Llama 3 70B Instruct vs Llama 3 8B Instruct
Llama 3 70B Instruct (2024) and Llama 3 8B Instruct (2024) are compact production models from AI at Meta. Llama 3 70B Instruct ships a 8K-token context window, while Llama 3 8B Instruct ships a 8K-token context window. On MMLU PRO, Llama 3 70B Instruct leads by 16.9 pts. On pricing, Llama 3 8B Instruct costs $0.03/1M input tokens versus $0.4/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama 3 8B Instruct is ~1233% cheaper at $0.03/1M; pay for Llama 3 70B Instruct only for provider fit.
Specs
| Released | 2024-04-18 | 2024-04-18 |
| Context window | 8K | 8K |
| Parameters | 70B | 8B |
| Architecture | decoder only | decoder only |
| License | Open Source | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Llama 3 70B Instruct | Llama 3 8B Instruct | |
|---|---|---|
| Input price | $0.4/1M tokens | $0.03/1M tokens |
| Output price | $0.4/1M tokens | $0.04/1M tokens |
| Providers |
Capabilities
| Llama 3 70B Instruct | Llama 3 8B Instruct | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Llama 3 70B Instruct | Llama 3 8B Instruct |
|---|---|---|
| MMLU PRO | 57.4 | 40.5 |
| HumanEval | 72.6 | 68.2 |
| Instruction-Following Evaluation | 77.8 | 59.5 |
| Massive Multitask Language Understanding | 82.0 | 76.9 |
Deep dive
On shared benchmark coverage, MMLU PRO has Llama 3 70B Instruct at 57.4 and Llama 3 8B Instruct at 40.5, with Llama 3 70B Instruct ahead by 16.9 points; HumanEval has Llama 3 70B Instruct at 72.6 and Llama 3 8B Instruct at 68.2, with Llama 3 70B Instruct ahead by 4.4 points; Instruction-Following Evaluation has Llama 3 70B Instruct at 77.8 and Llama 3 8B Instruct at 59.5, with Llama 3 70B Instruct ahead by 18.3 points. The largest visible gap is 18.3 points on Instruction-Following Evaluation, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint is close: both models cover structured outputs. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.
For cost, Llama 3 70B Instruct lists $0.4/1M input and $0.4/1M output tokens, while Llama 3 8B Instruct lists $0.03/1M input and $0.04/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3 8B Instruct lower by about $0.37 per million blended tokens. Availability is 18 providers versus 17, so concentration risk also matters.
Choose Llama 3 70B Instruct when provider fit and broader provider choice are central to the workload. Choose Llama 3 8B Instruct when provider fit and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Llama 3 70B Instruct or Llama 3 8B Instruct?
Llama 3 70B Instruct supports 8K tokens, while Llama 3 8B Instruct supports 8K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Llama 3 70B Instruct or Llama 3 8B Instruct?
Llama 3 8B Instruct is cheaper on tracked token pricing. Llama 3 70B Instruct costs $0.4/1M input and $0.4/1M output tokens. Llama 3 8B Instruct costs $0.03/1M input and $0.04/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 3 70B Instruct or Llama 3 8B Instruct open source?
Llama 3 70B Instruct is listed under Open Source. Llama 3 8B Instruct is listed under Open Source. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for structured outputs, Llama 3 70B Instruct or Llama 3 8B Instruct?
Both Llama 3 70B Instruct and Llama 3 8B Instruct expose structured outputs. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run Llama 3 70B Instruct and Llama 3 8B Instruct?
Llama 3 70B Instruct is available on GCP Vertex AI, AWS Bedrock, Microsoft Foundry, NVIDIA NIM, and DeepInfra. Llama 3 8B Instruct is available on AWS Bedrock, DeepInfra, OctoAI API, Fireworks AI, and Alibaba Cloud PAI-EAS. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Llama 3 70B Instruct over Llama 3 8B Instruct?
Llama 3 8B Instruct is ~1233% cheaper at $0.03/1M; pay for Llama 3 70B Instruct only for provider fit. If your workload also depends on provider fit, start with Llama 3 70B Instruct; if it depends on provider fit, run the same evaluation with Llama 3 8B Instruct.
Continue comparing
Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.